Assignment 1: Visual Analytics Theory

As outlined in grading and rules, to complete the course and take the credits, students should complete two assignments. This page describes the first (theory) assignment. The second (practical) assignment is described here.

Aims

As discussed during the course, design and evaluation are two critical components of a good visual analytics application. More specifically, a good application should

• be designed in such a way that it answers the original questions targeted by its users efficiently and effectively;
• avoid known pitfalls in various design aspects (visual encoding, interaction methods, scalability of presentation);
• be tested so that it is clear how efficient and effective it is for specific tasks.

To be able to construct good designs, one must first be able to evaluate existing designs (and, when limitations are found, to propose improvements). The aim of the theory assignment is to judge the skills of the student in evaluating and proposing improvements for existing visual analytics applications. The separate aim of testing the skills of actual application designs is evaluated separately by the practical assignment.

Steps

This assignment is described in detail in this accompanying document. In brief, the assignment steps, which follow a top-down structure, are as follows:

1. Choose an existing visualization

Choose an existing visualization solution (tool, online visualization) to work on. See the detailed description for constraints concerning the choice and pointers on where to choose visualizations from. The chosen visualization will be your study material (case study) for the rest of the assignment.

2. Describe the underlying problem

Analyze the visualization and related information (e.g. documentation, manuals, papers) to extract the questions that it aims to answer and tasks that it aims to support. This step is essential in the further evaluation of the effectiveness of the studied visualization (to find if something is effective, we first need to know what that something should support).

3. Describe the underlying data

Analyze the visualization and related information and produce a complete description of the data targeted by the visualization. Describe this data following the material presented in the course, both at dataset level (e.g. is the data tabular, multidimensional, time series, relational, etc) and at attribute level (which are the types and value-ranges of all attributes of all measurements). Ultimately your description should produce a data scheme of the studied application.

4. Study the proposed visual design

Analyze the visualization and produce a complete description of the different visual techniques that are used in its design. Describe these following the material presented in the course, at technique-class level (e.g. treemap, directed graph layout, bubble chart, timeline, etc); technique-details level (e.g. type of treemap algorithm being used, such as slice-and-dice vs squarified); and interaction level (e.g. type of workflow that connects the various views present in the application). Be as specific as possible.

5. Describe findings and propose improvements

Based on your findings so far, and on the insights you gathered by being an user (consumer) of the selected visualization, you need to complete two types of tasks. First, describe the actual findings you obtained by using the visualization (i.e., which are the answers of the questions found in step 2 that the visualization gave you, for the data at hand?). Secondly, describe the technical and/or design limitations that you found in the studied visualization, along the information found in step 4. For each such limitation, propose at least one alternative solution or visual design, and argue why your proposal would improve the visualization, along the overall drivers of efficiency and effectiveness.

Deliverables

The final deliverable for this assignment consists of

• a detailed report (PDF) describing all steps 1..5 of your assignment. Support the description of your results (and challenges found) by snapshots from your analyzed visualization, wherever this is appropriate. For more details on the structure and points to consider in your report, please consult the detailed assignment description.